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Practical Big Data Analytics

You're reading from   Practical Big Data Analytics Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781783554393
Length 412 pages
Edition 1st Edition
Languages
Concepts
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Author (1):
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Nataraj Dasgupta Nataraj Dasgupta
Author Profile Icon Nataraj Dasgupta
Nataraj Dasgupta
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Table of Contents (13) Chapters Close

Preface 1. Too Big or Not Too Big FREE CHAPTER 2. Big Data Mining for the Masses 3. The Analytics Toolkit 4. Big Data With Hadoop 5. Big Data Mining with NoSQL 6. Spark for Big Data Analytics 7. An Introduction to Machine Learning Concepts 8. Machine Learning Deep Dive 9. Enterprise Data Science 10. Closing Thoughts on Big Data 11. External Data Science Resources 12. Other Books You May Enjoy

Tutorial - associative rules mining with CMS data


This tutorial will implement an interface for accessing rules created using the Apriori Package in R.

We'll be downloading data from the CMS OpenPayments website. The site hosts data on payments made to physicians and hospitals by companies:

The site provides various ways of downloading data. Users can select the dataset of interest and download it manually. In our case, we will download the data using one of the Web-based APIs that is available to all users.

Downloading the data

The dataset can be downloaded either at the Unix terminal (in the virtual machine) or by accessing the site directly from the browser. If you are downloading the dataset in the Virtual Machine, run the following command in the terminal window:

time wget -O cms2016_2.csv 'https://openpaymentsdata.cms.gov/resource/vq63-hu5i.csv?$query=select Physician_First_Name as firstName,Physician_Last_Name as lastName,Recipient_City as city,Recipient_State as state,Submitting_Applicable_Manufacturer_or_Applicable_GPO_Name...
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